Technology
d790c9e6c0b5e02c87b375e782ac01bc-AuthorFeedback.pdf
Inourscenario,weassume24 the label of each support set is also given (eg, images of cat and the semantic label'cat'). We found this a realistic25 assumption. On the contrary, AM3 is model-28 agnostic toanymetric-based FSLmethods, asdescribed inthepaper. As pointed by R1 and R3, the proposed approach can potentially44 be used inmanydifferent cross-modal FSL settings involving visual and semantic information.
d77f00766fd3be3f2189c843a6af3fb2-AuthorFeedback.pdf
This part was poorly presented; we have updated the text[Update B]. To15 measure training instead of training confounded with issues of memorization vs. generalization, we use thetrain16 gradients instead ofval. Observations like the last layer hurting are also more surprising on train vs. val. We use17 full-batchgradients for analysis instead of single mini-batch gradient to measure learning in as noise-free a way as18 possible. First order was only mentioned as an example to illustrate the concept.22
Are lasers the future of anti-drone warfare?
Are lasers the future of anti-drone warfare? A drone appears on the grainy, gray-scaled image of the thermal camera. This is the type of drone used by groups such as Hezbollah, Hamas and the Yemeni Houthis. Seconds later, the wing of the drone snaps off, sending it tumbling down, exploding when it hits the ground. This is a video shared by the Israeli Ministry of Defence and arms producer Rafael, a hint towards the future of anti-drone warfare.
Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation
The ability to collect a large dataset of human preferences from text-to-image users is usually limited to companies, making such datasets inaccessible to the public. To address this issue, we create a web app that enables text-to-image users to generate images and specify their preferences. Using this web app we build Pick-a-Pic, a large, open dataset of text-to-image prompts and real users'